Publication detail

Do 'complex' financial models really lead to complex dynamics? Agent-based models and multifractality

Author(s): prof. PhDr. Ladislav Krištoufek Ph.D.,
PhDr. Jiří Kukačka Ph.D.,
Type: Articles in journals with impact factor
Year: 2020
Number: 113
Published in: Journal of Economic Dynamics and Control, 113C, 103855, DOI
Publishing place:
Keywords: complex systems, financial agent-based models, time series analysis, multifractal analysis, detrended fluctuation analysis
JEL codes: C13, C22, C63, D84, G02, G17
Suggested Citation: Kukacka, J., Kristoufek, L. (2020). Do 'complex' financial models really lead to complex dynamics? Agent-based models and multifractality. Journal of Economic Dynamics and Control, 113C, 103855.
Grants: PRIMUS/19/HUM/17 2019-2021 Behavioral finance and macroeconomics: New insights for the mainstream
Abstract: Agent-based models are usually claimed to generate complex dynamics; however, the link to such complexity has not been subject to rigorous examination. This paper studies this link between the complexity of financial time series---measured by their multifractal properties---and the design of various small-scale agent-based frameworks used to model the heterogeneity of financial markets. Nine popular models are analyzed, and while some of the models do not generate interesting multifractal patterns, we observe the strongest tendency towards multifractal behavior for the Bornholdt Ising model, the discrete choice-based models by Gaunersdorfer & Hommes and Schmitt & Westerhoff, and the transition probabilities-based framework by Franke & Westerhoff. Complexity is thus not an automatic feature of the time series generated by any agent-based model but generated only by models with specific properties. In addition, because multifractality is considered a financial stylized fact, its presence can be used as a new means to validate such models.




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